Model Parameters

Row

Model Parameters

Model Instance

  • Planning horizon is decreased from 24 weeks to 10 weeks
  • Maximum tracked wait is decreased from 6 weeks to 4 weeks
  • There are 3 surgeries instead of 6 surgeries
  • Number of priorities is set to 1

Simulation Parameters

  • 30 Replications
  • 1000 weeks duration
  • 250 weeks warm up

Surgeries

  • Surgery 1 - 1. SPINE POSTERIOR DECOMPRESSION/LAMINECTOMY LUMBAR
  • Surgery 4 - 4. SPINE POST CERV DECOMPRESSION AND FUSION W INSTR
  • Surgery 6 - 6. SPINE POSTERIOR DISCECTOMY LUMBAR

Arrival Rate

It was set to be 95% of the capacity, however due to transitions, the resource usage should be higher than 95%
Surgery Complexity Arrival_Adjusted Arrival_Original Rationale
Surgery 1 Complexity 1 1.23 1.0000 once per week
Surgery 1 Complexity 2 0.62 0.5000 once per two weeks
Surgery 4 Complexity 1 0.14 0.0833 once per 3 months
Surgery 4 Complexity 2 0.10 0.0625 once per 4 months
Surgery 6 Complexity 1 1.23 1.0000 once per week
Surgery 6 Complexity 2 0.62 0.5000 once per 2 weeks

Row

Resource Usage

Surgery Complexity Resource_Type Usage
Surgery 1 Complexity 1 Admissions 0.0
Surgery 1 Complexity 1 OR_Time 3.0
Surgery 1 Complexity 2 Admissions 1.0
Surgery 1 Complexity 2 OR_Time 4.0
Surgery 4 Complexity 1 Admissions 1.0
Surgery 4 Complexity 1 OR_Time 4.0
Surgery 4 Complexity 2 Admissions 1.0
Surgery 4 Complexity 2 OR_Time 5.5
Surgery 6 Complexity 1 Admissions 0.0
Surgery 6 Complexity 1 OR_Time 1.5
Surgery 6 Complexity 2 Admissions 0.0
Surgery 6 Complexity 2 OR_Time 2.5

Resource Capacity

Resouce Capacity_Weekly Unit
Admissions 1.50 Patients Admitted per week
OR_Time 11.25 OR Hours per week

NP, 1

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 11.83 += 14.91 19.71 += 19.68 36.56 += 19.35 0.59 += 0.22
myopic 14.15 += 12.53 24.2 += 17.01 26.3 += 8.32 2.36 += 0.86

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 47.68 += 9.53 37.7 += 8.96 8.9 += 2.42 1.09 += 0.45
myopic 56.53 += 11.18 45.76 += 10.22 6.43 += 1.46 4.35 += 0.85

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.96 += 0.1 1.04 += 0.11 23.25 += 1.11 0.1 += 0.03
myopic 10.06 += 0.43 12.58 += 0.6 42.65 += 2.2 3.2 += 0.2

Utilization

policy bed OR
MDP 53.51 += 12.85 93.48 += 7.07
myopic 64.89 += 11.87 95.48 += 6.82

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 3.09 += 0.09 4.4 += 0.19 5.22 += 0.6 1.47 += 0.1
myopic 12.82 += 0.33 15.3 += 0.38 62.53 += 2.78 3.8 += 0.22

Wait List Size by Group

Reschedules by Group

NP, 1.1

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.41 += 1.55 2.29 += 2.14 2.61 += 1.26 0.37 += 0.19
myopic 1.64 += 0.87 2.23 += 0.96 4.19 += 1.51 0.72 += 0.38

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 5.58 += 1.97 4.27 += 1.71 0.63 += 0.34 0.68 += 0.36
myopic 6.5 += 2.11 4.16 += 1.39 1.01 += 0.45 1.32 += 0.63

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.5 += 0.06 0.28 += 0.06 5.65 += 0.76 0.04 += 0.02
myopic 2.22 += 0.22 2.36 += 0.26 13.3 += 1.4 0.62 += 0.12

Utilization

policy bed OR
MDP 57.33 += 13.38 86.51 += 8.1
myopic 58.69 += 10.8 86.85 += 7.59

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.25 += 0.07 1.66 += 0.13 3.09 += 0.44 0.58 += 0.08
myopic 3.93 += 0.26 5.48 += 0.36 11.91 += 1.36 1.31 += 0.14

Wait List Size by Group

Reschedules by Group

NP, 1.2

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.58 += 0.56 0.82 += 0.7 1.51 += 0.9 0.22 += 0.15
myopic 0.82 += 0.48 1.15 += 0.54 2.27 += 0.76 0.29 += 0.21

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 2.3 += 1 1.53 += 0.76 0.36 += 0.25 0.4 += 0.28
myopic 3.22 += 1.19 2.14 += 0.82 0.55 += 0.3 0.53 += 0.38

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.2 += 0.03 0.09 += 0.02 2.45 += 0.4 0.01 += 0.01
myopic 0.79 += 0.09 0.54 += 0.11 7.88 += 0.87 0.11 += 0.04

Utilization

policy bed OR
MDP 57.32 += 14.26 79.23 += 8.89
myopic 57.47 += 11.04 79.31 += 8.21

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.51 += 0.06 0.7 += 0.09 1.39 += 0.36 0.19 += 0.04
myopic 1.51 += 0.14 2.38 += 0.22 3.46 += 0.57 0.36 += 0.07

Wait List Size by Group

Reschedules by Group

NP, 1.3

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.36 += 0.37 0.51 += 0.48 0.88 += 0.46 0.13 += 0.12
myopic 0.56 += 0.39 0.81 += 0.45 1.77 += 0.62 0.14 += 0.13

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.41 += 0.72 0.96 += 0.55 0.21 += 0.18 0.25 += 0.21
myopic 2.19 += 0.87 1.51 += 0.64 0.43 += 0.26 0.25 += 0.24

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.08 += 0.02 0.02 += 0.01 1.15 += 0.31 0 += 0
myopic 0.4 += 0.05 0.15 += 0.04 5.31 += 0.63 0.02 += 0.01

Utilization

policy bed OR
MDP 57.3 += 14.98 73.11 += 9.21
myopic 57.28 += 11.45 73.13 += 8.49

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.16 += 0.03 0.22 += 0.05 0.59 += 0.27 0.05 += 0.02
myopic 0.53 += 0.06 0.85 += 0.11 1.49 += 0.37 0.09 += 0.03

Wait List Size by Group

Reschedules by Group

P, 1

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 11.87 += 8.68 16.33 += 5.53 31.65 += 27.69 4.74 += 3.77
myopic 22.21 += 16.42 16.4 += 5.38 75.42 += 51.36 21.12 += 12.27

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 47.32 += 9.29 30.63 += 5.47 7.78 += 3.7 8.92 += 3.2
myopic 88.6 += 20.81 30.81 += 6.06 18.66 += 7.93 39.14 += 9.61

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 26.33 += 0.98 52.45 += 1.99 0.07 += 0.09 3.27 += 0.28
myopic 31.54 += 2.63 53.06 += 4.56 9.19 += 1.67 12.64 += 0.89

Utilization

policy bed OR
MDP 119.93 += 12.07 102.53 += 8.47
myopic 117.43 += 13.99 100.2 += 6.89

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 64.54 += 1.64 52.17 += 3 0 += NA 85.44 += 5.78
myopic 78.62 += 4.05 46.86 += 7 0 += NA 121.15 += 14.38

Wait List Size by Group

Reschedules by Group

P, 1.1

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 3.45 += 1.95 5.22 += 2.45 0.96 += 1.44 1.98 += 0.98
myopic 1.43 += 0.92 1.77 += 1.1 0.33 += 0.33 1.23 += 0.72

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 13.62 += 3.45 9.75 += 2.7 0.23 += 0.26 3.64 += 1.35
myopic 5.66 += 2.36 3.32 += 1.4 0.08 += 0.11 2.27 += 1.1

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 10.83 += 0.72 20.86 += 1.44 0.02 += 0.03 2.07 += 0.15
myopic 3.3 += 0.46 5.72 += 0.76 0.23 += 0.14 1.25 += 0.23

Utilization

policy bed OR
MDP 81.2 += 19.25 89.23 += 11.1
myopic 62.65 += 19.18 87.11 += 8.43

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 35.69 += 1.28 46.42 += 1.61 0 += NA 29.48 += 1.9
myopic 21.91 += 1.47 35.4 += 2.2 0 += NA 11.1 += 1.09

Wait List Size by Group

Reschedules by Group

P, 1.2

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.69 += 1.11 2.1 += 1.38 0.28 += 0.46 1.45 += 0.79
myopic 0.6 += 0.41 0.76 += 0.5 0.24 += 0.24 0.48 += 0.29

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 6.65 += 2.72 3.92 += 1.82 0.07 += 0.12 2.66 += 1.21
myopic 2.37 += 1.19 1.42 += 0.76 0.06 += 0.1 0.88 += 0.54

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 4.14 += 0.44 7.43 += 0.81 0 += 0 1.33 += 0.15
myopic 0.85 += 0.12 1.53 += 0.22 0.23 += 0.18 0.25 += 0.07

Utilization

policy bed OR
MDP 65.1 += 19.25 79.95 += 11.29
myopic 58.29 += 18.85 79.28 += 9.17

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 19.91 += 1.19 11.8 += 0.72 0 += NA 30.78 += 2.09
myopic 9.54 += 0.68 16.25 += 1.14 0 += NA 3.99 += 0.37

Wait List Size by Group

Reschedules by Group

P, 1.3

Row

Policy Description

The policy description is based on a graph to the right

  • The left column shows MDP policy, the right column shows Myopic Policy
  • The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
  • The bottom row shows in which days the policy will allow scheduling.
  • The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making

Policy Math Graph

Policy Evidence Graph

Row

Wait Times in weeks

policy Overall Surgery1 Surgery4 Surgery6
MDP 0.75 += 0.61 0.91 += 0.76 0.14 += 0.18 0.66 += 0.44
myopic 0.34 += 0.26 0.44 += 0.31 0.23 += 0.23 0.26 += 0.19

Wait List Size

policy Overall Surgery1 Surgery4 Surgery6
MDP 2.94 += 1.63 1.7 += 1.06 0.03 += 0.07 1.21 += 0.77
myopic 1.35 += 0.81 0.83 += 0.53 0.06 += 0.09 0.47 += 0.37

Transitions per week

policy Overall Surgery1 Surgery4 Surgery6
MDP 1.56 += 0.19 2.72 += 0.33 0.02 += 0.03 0.57 += 0.1
myopic 0.35 += 0.07 0.64 += 0.13 0.14 += 0.09 0.08 += 0.03

Utilization

policy bed OR
MDP 59.86 += 18.93 73.33 += 10.67
myopic 57.62 += 18.8 73.1 += 9.47

Row

Reschedules

policy Overall Surgery1 Surgery4 Surgery6
MDP 8.34 += 0.54 11.98 += 0.8 0 += NA 5.74 += 0.51
myopic 4.26 += 0.43 7.63 += 0.77 0 += NA 1.4 += 0.21

Wait List Size by Group

Reschedules by Group

---
title: "Report"
date: "`r Sys.Date()`"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
## Global options
library(reticulate)
library(knitr)
library(flexdashboard)
library(scales)
library(here)
library(tidyverse)
library(readr)
library(plotly)
library(tidyverse)
knitr::opts_chunk$set(cache = TRUE)
source(here('modules','data_funcs.R'))

# PARAMS
warm <- 250
dur <- 1000
repl <- 30
path <- here('data','full-sm')



# NO CUU - OR * 1
modif <- '0-1'
dt_pl_n10 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_n10 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_n10 <- generate_summary_zs(path, modif, FALSE)

# NO CUU - OR * 1.1
modif <- '0-1.1'
dt_pl_n11 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_n11 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_n11 <- generate_summary_zs(path, modif, FALSE)

# NO CUU - OR * 1.2
modif <- '0-1.2'
dt_pl_n12 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_n12 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_n12 <- generate_summary_zs(path, modif, FALSE)

# NO CUU - OR * 1.3
modif <- '0-1.3'
dt_pl_n13 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_n13 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_n13 <- generate_summary_zs(path, modif, FALSE)



# CUU - OR * 1
modif <- '1000-1'
dt_pl_y10 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_y10 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_y10 <- generate_summary_zs(path, modif, TRUE)

# CUU - OR * 1.1
modif <- '1000-1.1'
dt_pl_y11 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_y11 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_y11 <- generate_summary_zs(path, modif, TRUE)

# CUU - OR * 1.2
modif <- '1000-1.2'
dt_pl_y12 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_y12 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_y12 <- generate_summary_zs(path, modif, TRUE)

# CUU - OR * 1.3
modif <- '1000-1.3'
dt_pl_y13 <- generate_summary(path, modif, dur, warm, repl)
dt_sa_y13 <- generate_summary_sa(path, modif, dur, warm, repl)
dt_zs_y13 <- generate_summary_zs(path, modif, TRUE)



# MODEL DATA SUMMARY
arrival_rate <- data.frame(
  Surgery = c('Surgery 1', 'Surgery 1', 'Surgery 4', 
              'Surgery 4', 'Surgery 6', 'Surgery 6'),
  Complexity = c('Complexity 1', 'Complexity 2', 'Complexity 1', 
                 'Complexity 2', 'Complexity 1', 'Complexity 2'),
  "Arrival_Adjusted" = c(1.23, 0.62, 0.14, 0.10, 1.23, 0.62),
  "Arrival_Original" = c(1, 0.5, 0.0833, 0.0625, 1, 0.5), 
  Rationale = c("once per week", "once per two weeks", "once per 3 months", 
                "once per 4 months", "once per week", "once per 2 weeks")
)

resource_usage <- data.frame(
  Surgery = c('Surgery 1', 'Surgery 1', 'Surgery 1', 'Surgery 1', 
              'Surgery 4', 'Surgery 4', 'Surgery 4', 'Surgery 4', 
              'Surgery 6', 'Surgery 6', 'Surgery 6', 'Surgery 6'),
  Complexity = c('Complexity 1', 'Complexity 1', 'Complexity 2', 
                 'Complexity 2', 'Complexity 1', 'Complexity 1', 
                 'Complexity 2', 'Complexity 2', 'Complexity 1', 
                 'Complexity 1', 'Complexity 2', 'Complexity 2'),
  Resource_Type = c('Admissions', 'OR_Time','Admissions', 'OR_Time',
                    'Admissions', 'OR_Time','Admissions', 'OR_Time',
                    'Admissions', 'OR_Time','Admissions', 'OR_Time'), 
  Usage = c(0,3,1,4,1,4,1,5.5,0,1.5,0,2.5)
)

resource_capacity <- data.frame(
  Resouce = c('Admissions', 'OR_Time'),
  Capacity_Weekly = c(1.5, 11.25),
  Unit = c("Patients Admitted per week", "OR Hours per week")
)
```

Model Parameters
=======================================================================

Row
-----------------------------------------------------------------------

### Model Parameters
**Model Instance**

* Planning horizon is decreased from 24 weeks to 10 weeks
* Maximum tracked wait is decreased from 6 weeks to 4 weeks
* There are 3 surgeries instead of 6 surgeries
* Number of priorities is set to 1

**Simulation Parameters**

* 30 Replications
* 1000 weeks duration
* 250 weeks warm up

**Surgeries**

* Surgery 1 - 1. SPINE POSTERIOR DECOMPRESSION/LAMINECTOMY LUMBAR
* Surgery 4 - 4. SPINE POST CERV DECOMPRESSION AND FUSION W INSTR
* Surgery 6 - 6. SPINE POSTERIOR DISCECTOMY LUMBAR

### Arrival Rate
It was set to be 95% of the capacity, however due to transitions, the resource usage should be higher than 95%
``` {r echo=FALSE, cache=FALSE}
kable(arrival_rate)
```

Row
-----------------------------------------------------------------------

### Resource Usage
```{r echo=FALSE, cache=FALSE}
kable(resource_usage)
```

### Resource Capacity
```{r echo=FALSE, cache=FALSE}
kable(resource_capacity)
```





NP, 1
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_n10$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_n10$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n10$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n10$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n10$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n10$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n10$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n10$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n10$res_plot$rsc_plt %>% ggplotly()
```





NP, 1.1
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_n11$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_n11$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n11$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n11$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n11$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n11$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n11$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n11$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n11$res_plot$rsc_plt %>% ggplotly()
```





NP, 1.2
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_n12$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_n12$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n12$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n12$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n12$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n12$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n12$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n12$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n12$res_plot$rsc_plt %>% ggplotly()
```





NP, 1.3
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_n13$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_n13$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n13$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n13$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n13$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n13$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_n13$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n13$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_n13$res_plot$rsc_plt %>% ggplotly()
```





P, 1
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_y10$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_y10$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y10$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y10$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y10$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y10$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y10$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y10$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y10$res_plot$rsc_plt %>% ggplotly()
```





P, 1.1
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_y11$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_y11$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y11$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y11$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y11$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y11$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y11$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y11$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y11$res_plot$rsc_plt %>% ggplotly()
```





P, 1.2
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_y12$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_y12$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y12$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y12$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y12$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y12$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y12$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y12$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y12$res_plot$rsc_plt %>% ggplotly()
```





P, 1.3
=======================================================================

Row {data-height=650}
-----------------------------------------------------------------------

### Policy Description
The policy description is based on a graph to the right

* The left column shows MDP policy, the right column shows Myopic Policy
* The top row shows scheduling costs, adjusted for resource usage, the bottom is not adjusted
* The bottom row shows in which days the policy will allow scheduling.
* The top row shows approximate order of patient scheduling.

Additionally the far right graph shows the approximate decision making 

### Policy Math Graph

```{r echo=FALSE}
dt_zs_y13$zf_plt %>% ggplotly()
```

### Policy Evidence Graph

```{r echo=FALSE}
dt_sa_y13$res_plot$sched_plt %>% ggplotly()
```

Row 
-----------------------------------------------------------------------

### Wait Times in weeks
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y13$results$pw)
```

### Wait List Size
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y13$results$wtl)
```

### Transitions per week
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y13$results$tr)
```

### Utilization
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y13$results$util)
```

Row
-----------------------------------------------------------------------

### Reschedules
```{r echo=FALSE, cache=FALSE}
kable(dt_pl_y13$results$rsc)
```

### Wait List Size by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y13$res_plot$waitlist_plt %>% ggplotly()
```

### Reschedules by Group
```{r echo=FALSE, cache=FALSE}
dt_sa_y13$res_plot$rsc_plt %>% ggplotly()
```